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Analysis of correlated data with feedback for time-dependent covariates in psychiatry research
In studies on psychiatry and neurodegenerative diseases, it is common to have data that are correlated due to the hierarchical structure in data collection or to repeated measures on the subject longitudinally. However, the feedback effect created due to time-dependent covariates in these studies is...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BMJ Publishing Group
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477964/ https://www.ncbi.nlm.nih.gov/pubmed/32914055 http://dx.doi.org/10.1136/gpsych-2020-100263 |
| Sumario: | In studies on psychiatry and neurodegenerative diseases, it is common to have data that are correlated due to the hierarchical structure in data collection or to repeated measures on the subject longitudinally. However, the feedback effect created due to time-dependent covariates in these studies is often overlooked and seldom modelled. This article reviews the methodological development of feedback effects with marginal models for longitudinal data and discusses their implementation. |
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